A numerical method for spherical particle motion in turbulent flow with large Reynolds number

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南京市大气PM2.5时空分布特征与潜在源区贡献分析

对2017年南京市区7个自动空气质量监测点的PM_(2.5)质量浓度ρ(PM_(2.5))数据进行分析,采用克里金(Kringing)空间插值法、气流运动轨迹聚类、潜在源贡献因子法(PSCF)和浓度权重轨迹分析法(CWT)探讨了四季大气中ρ(PM_(2.5))的时空分布特征和潜在来源。结果显示,四季大气中ρ(PM_(2.5))均值由高到低依次为冬季(65. 54μg/m~3)、春季(41. 70μg/m~3)、秋季(35. 18μg/m~3)和夏季(23. 56μg/m~3),秦淮区四季大气中ρ(PM_(2.5))均最高。春季南京大气中ρ(PM_(2.5))易受黄海海岸和北方大陆性输送气流的影响,来自黄海方向的气流轨迹2贡献比例达51. 65%,对应的ρ(PM_(2.5))为50. 91μg/m~3;夏季南京大气中ρ(PM_(2.5))主要受江苏、东部海洋和南部沿海城市输送气流的影响,其中源自江苏的气流轨迹1对南京大气PM_(2.5)贡献比例最大(33. 64%),气流轨迹对应的ρ(PM_(2.5))为35μg/m~3;秋季南京大气中ρ(PM_(2.5))易受短距离的偏北气流影响,来自山西南部,河南中部、安徽中部的气流轨迹5对应的ρ(PM_(2.5))最高,出现概率(21. 11%)和贡献比例(27. 81%)均较高;冬季南京大气中ρ(PM_(2.5))主要受北方大陆性输送气流影响,来自俄罗斯、蒙古国东部、河北北部、北京、天津、山东中部的长距离气流轨迹4对应的ρ(PM_(2.5))最高,达109. 8μg/m~3,其贡献比例为26. 86%。PSCF和CWT分析发现,安徽、山东、浙江与江苏交界和黄海海岸是影响南京市空气质量的主要潜在源区,此外,湖北、北京、天津以及渤海海岸也是南京大气PM_(2.5)的潜在源区。     

低通时序滤波轨线法在太湖营养过程识别中的应用

环境背景条件变化会导致湖泊ρ（Chla）与环境因子响应关系发生变化.采用低通时序滤波轨线方法可以方便地识别ρ（Chla）与环境因子响应关系的时间转折点,将长时间序列数据进行分段,从而建立分段回归函数,为研究环境因子与湖泊ρ（Chla）的因果关系提供了一种新的思路.以太湖为研究对象,采用低通时序滤波轨线方法,评估了2001—2018年太湖的ρ（Chla）与营养盐〔ρ（TN）、ρ（TP）〕以及氮磷比〔ρ（TN）/ρ（TP）〕的变化过程,研究了年均气温、滞留时间对产藻效率〔ρ（Chla）/ρ（TP）〕的影响过程.结果表明:①2006年、2011年为太湖营养过程轨线的两个时间转折点,将太湖的营养过程轨线分为3段.第1段为污染阶段（2001—2006年）,太湖的ρ（TN）、ρ（TP）、ρ（Chla）同步升高,于2006年达到第一个峰值;第2段为修复阶段（2006—2011年）,太湖的ρ（TN）、ρ（TP）、ρ（Chla）同步降低,于2011年达到谷值;第3段为富营养化加剧阶段（2011—2018年）,太湖的ρ（TN）呈下降趋势,ρ（TP）与ρ（Chla）同步升高,至今未出现转折点.②太湖藻类生长的限值因子为ρ（TP）,2011年之后氮磷比进入浮游藻类适宜生长区,为蓝藻暴发提供了条件.③2011—2018年产藻效率增长了51%,且目前仍在升高未出现转折点,气温升高可能是主要原因.④依据2011—2018年的滤波值建立ρ（Chla）-ρ（TP）的函数预测,为控制蓝藻暴发〔ρ（Chla） < 10 mg/m3〕,太湖的ρ（TP）需要控制在52 μg/L以下.⑤2006年后,太湖的滞留时间呈现缩短趋势,对藻类的繁殖形成抑制,但滞留时间不是影响产藻效率的关键因子.研究显示:自2006年太湖流域实施一系列生态修复工程后,湖泊氮浓度明显降低,但由于流域氮磷排放量较大而且湖体沉积物中累积磷含量较高,致使水体营养盐水平仍未降到能显著抑制蓝藻生长的水平;目前气温升高趋势仍在持续,太湖的控藻形势严峻,为摆脱气候变暖对蓝藻水华趋势的决定作用,应当在控氮基础上加大控磷的力度,同时更多考虑水文调节、生物修复、加强打捞等措施.      

长株潭城市群气溶胶时空分布与传输规律

为研究长株潭城市群大气污染时空演化特征及潜在传输规律,采用2008~2016年中分辨率成像光谱仪（MODIS）MAIAC气溶胶光学厚度（AOD）数据,分析长株潭城市群近10a来AOD演化特征.在此基础上,利用拉格朗日混合型单粒子轨迹模式（HYSPLIT）及全球资料同化系统（GDAS）气象要素数据研究大气污染物潜在传输规律.结果表明,长株潭城市群AOD呈现下降趋势,并以春、夏季下降幅度最为显著.空间上,AOD总体呈北高南低、西高东低分布特征,并与经济发展、城市化水平等因素密切相关.此外,长株潭城市群大气污染物向外长距离传输（>1500km）、中距离传输（500~1500km）以及局地传输（0~500km）比率分别为17.89%、36.45%和45.66%,主要影响湖北、江西、安徽、广东、广西、江苏和浙江等地区.研究结果有助于理解长株潭城市群大气污染的时空变化规律,同时为区域“联防联控”、建设“美丽中国”提供科学的辅助依据.     

2014~2017年北京城区霾污染态势及潜在来源

统计分析2014~2017年北京城区霾污染发生情况,利用HYSPLIT模式对4年内气流来向进行聚类计算,识别区域内的主要污染传输通道和潜在污染源区分布及变化.结果显示,研究期间北京市城区空气质量状况整体呈改善趋势,灰霾时发生率从2014年的50.6%降至2017年33.7%,灰霾日数由165d降至78d,每年10月到次年采暖结束的3月灰霾发生较为集中.不同强度霾发生频率逐年下降,秋、冬季灰霾发生频率及污染强度均逐步降低.冀东南平原区、太行山东麓以及燕山南麓沿线为京津冀地区的3条主要污染传输通道,传输高度均在近地1000m内,期间通道轨迹对应北京城区PM_2.5平均达124.1μg/m³,其出现频率在2014~2017年逐年减小,并且各年当中同类轨迹所对应的北京PM_2.5均呈逐年下降趋势.北京城区PM_2.5的主要潜在源区从华北平原和渤海天津港区域逐渐缩小至冀中南和鲁西北地区,且传输通道区域污染贡献率逐年降低,有利的天气形势和人为的区域减排是近年空气质量改善的2大主因.     

常州市冬季大气污染特征及潜在源区分析

为了解常州市冬季大气污染特征,对2013—2015年常州市冬季PM_2.5、PM₁₀、SO₂、NO₂、CO数据进行分析,并结合HYSPLIT 4.9模式研究不同气团来源对常州市各污染物浓度的影响及潜在污染源区分布特征.结果表明,常州市冬季以PM_2.5污染为主,其占冬季首要污染物的90%以上,冬季PM_2.5小时浓度对应的空气质量级别以良和轻度污染出现频次最多,冬季的ρ（PM_2.5）对ρ（PM_2.5）年均值的贡献率高达37.4%,不完全燃烧是颗粒物的一个重要来源.冬季ρ（PM_2.5）、ρ（PM₁₀）、ρ（SO₂）、ρ（NO₂）和ρ（CO）的日变化均呈双峰分布,两个峰值分别出现在交通的早高峰和晚高峰附近.ρ（NO₂）在晚高峰明显大于早高峰,而ρ（SO₂）和ρ（CO）表现为早高峰大于晚高峰.常州市CO/NO_x和SO₂/NO_x的分析结果表明,常州市交通源的贡献明显,点源对常州市的空气质量的影响也较大.1和6 h的ρ（PM_2.5）梯度变化可判识细颗粒物的爆发性增长.冬季常州市受到西北、西和西南等地区的大陆性气流影响较大,其对应的ρ（PM_2.5）、ρ（PM₁₀）、ρ（SO₂）、ρ（NO₂）和ρ（CO）平均值相对较高,且对应的污染轨迹出现概率较大.偏东方向的气流由于移动速度慢,不利于污染物扩散易造成污染累积,导致ρ（PM_2.5）、ρ（SO₂）和ρ（NO₂）相对较高.WPSCF（源区分布概率）高值区（>0.5）集中于从芜湖至上海的长江中下游区域和杭州湾区域.PM_2.5、PM₁₀、SO₂、NO₂和CO潜在源区存在较大差异性,NO₂、SO₂和CO本地化的潜在贡献较PM_2.5和PM₁₀更明显.此外,受船舶等影响海洋源区对NO₂、SO₂和CO的潜在贡献较大.研究显示,长三角区域的大气污染物以本地污染为主,但远距离污染输送贡献也不容忽视.      

河北省涞水县大气颗粒物单颗粒分析表征及来源识别

为了解河北省涞水县颗粒物污染特征,采用单颗粒分析技术扫描电镜-X射线能谱法和气团后向轨迹分析技术对该县2015年3个典型污染时段〔即正常管控、严格管控（2015年阅兵期间）及发生严重颗粒物染污〕采集的7个大气颗粒物样品进行了分析表征和来源解析.共测量了1 506个粒径≥0.5 μm的单颗粒,其中粒径小于2.5 μm的颗粒占98%以上,测量结果揭示了细颗粒污染特征.结果表明:①碳质颗粒为主要颗粒物种类,其检出数目占比在90%以上.②非供暖期严格管控时段,当地居民日常生活产生的球形碳质颗粒检出数目占比最高.③非供暖期正常管控时段,机动车排放的碳质集合体颗粒检出数目占比最高,交通污染贡献最大.④供暖期球形碳质颗粒检出数目占比最高,含硫颗粒检出数目占比相对增加,燃煤的贡献最大.3个采样时段48 h气团后向轨迹分析结果表明,在空气质量良好、颗粒物污染水平较低的情况下,影响研究区域空气质量的主要是本地源;雾霾天气（处于严重颗粒物污染时段）时,西南方向外来源和本地源共同构成研究区域的颗粒物污染状态.      

Dry deposition of PM10 over the Yellow Sea during Asian dust events from 2001 to 2007

Dry deposition velocities and fluxes of PM10during Asian dust events over the Yellow Sea from 2001 to 2007 were investigated using observation data in Qingdao, China and Jeju, Korea. The dry deposition velocities of PM10 during dust events over the Yellow Sea ranged from 0.19 to 8.17 cm/sec, with an average of 3.38 cm/sec. Dry deposition fluxes of PM10during dust events over the Yellow Sea were in the range of 68.5–2647.1 mg/(m2·day), with an average of 545.4 mg/(m2·day), which is 2–10 times higher than those reported by other studies for both dust and non-dust periods. It was estimated that 2.6 × 1011–48.7 × 1011g dust particles deposit to the Yellow Sea during dust events through dry deposition every year. Compared with the results in previous studies, it was found that the dry deposition of PM10over the Yellow Sea during dust events in the years with high frequency of dust could account for a large or overwhelming fraction of the annual total dry deposition. Backward air mass trajectory analysis showed that dust events influenced Jeju mainly originated from the desert regions located in Mongolia and Inner Mongolia, China. There were 119 backward trajectories influenced both Qingdao and Jeju during 15 dust events from 2001 to 2007, accounting for 61.3% of the total trajectories of 194, indicating that Qingdao and Jeju were usually on the same pathway of dust transport downwind from source areas.     

Intra‐individual variability in job complexity over time: Examining the effect of job complexity trajectory on employee job strain

Drawing on gestalt characteristics theory, we advance the literature on the effect of job complexity on employee well‐being by considering intra‐individual variability of job complexity over time. Specifically, we examine how the trend, or trajectory, of job complexity over time can explain unique variance of employee job strain. Across two longitudinal data sets, we consistently find that, with the average level of job complexity during a given period held constant, a positive job complexity trajectory (i.e., an increasing trend in complexity) is associated with higher employee job strain. Based on job‐demand‐control theory and the exposure‐reactivity model, we further establish that job autonomy and employee emotional stability jointly moderate the relationship between job complexity trajectory and employee job strain. Specifically, for employees with high emotional stability, job autonomy mitigates the job strain brought by positive job complexity trajectory, whereas for employees with low emotional stability, job autonomy does not help to reduce the adverse effect of the increasing trend. These findings not only contribute to extend the understanding of the job complexity – strain relationship, but also suggest a promising, dynamic avenue to study the effects of work characteristics on employee well‐being as well as other outcomes. Copyright © 2016 John Wiley & Sons, Ltd.     

Analysis and Case Study of Duststorms in the Beijing Area

Dust weather conditions with strong wind often occur in Beijing during spring. The number of duststorms in Beijing has declined since 1954. In the last two years, however, the number of duststorms in Beijing has increased drastically due to frequent cold air movements and the deteriorated ecological environment. The heaviest duststorm in the last decade in Beijing occurred on 6 April 2000. It was caused by the development of a high-level small trough along with strong northwest wind behind a large trough that moved eastward and developed a strong cold air system. A non-hydrostatic meso-scale numerical model (MM5) gave a good forecast to the duststorm's major features and movement. Simulated results showed that there was a strong vertical ascending motion with a strong positive vorticity center in mid and low level. The mesoscale structure's formation and development and movement were consistent with the passage and moving direction of the duststorm. At the same time, the trajectories of air particles during this duststorm event and another case (on 27 March 2000) were estimated and analyzed, which had the comparable results with the real situation and the trajectory monitored by meteorological satellite. The trajectories analysis could help us study the transport track and sand source to some extent.